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intel_pytorch_2.1.0a0
intel_tensorflow_2.14.0
intel_jax_0.4.20
| Hinweis |
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Please note that PVC nodes currently run on Rocky 8 linux, and so only python versions <=3.9 are supported. |
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NumPy 2.0.0 breaks binary backwards compatibility. If Numpy-related runtime errors are encountered, please consider downgrading to a version <2.0.0 |
Pytorch
Load the Intel OneAPI module and create a new conda environment within your Intel python distribution:
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pip install tensorflow==2.14.0
pip install --upgrade intel-extension-for-tensorflow[xpu]==2.14.0 |
This installs TensorFlow together with it's Intel extension necessary to run non-CUDA operations on Intel GPUs. On a compute node, the presence of GPUs can be assessed:
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| Hinweis |
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Intel XPU support is still experimental for JAX, as of version 0.4.20 |
Like Pytorch and TensorFlow, JAX also has an extension via OpenXLA. To prepare a JAX environment for use with Intel GPUs, first create a new conda environment:
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Once the environment is activated, the following commands install JAX
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pip install numpy==1.24.4 pip install jax==0.4.20 jaxlib==0.4.20 pip install --upgrade intel-_extension-_for-openxla_openxla==0.2.1 |
This installs JAX together with its Intel extension necessary to run non-CUDA operations on Intel GPUs. On a compute node, the presence of GPUs can be assessed:
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